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Do informal risk-sharing groups reduce the challenge of providing weather indexed insurance products?

Evidence from a randomized field experiment in Ethiopia

Guush Berhane, Daniel Clarke,Stefan Dercon, Ruth Vargas Hill and

Alemayehu Seyoum Taffesse

I4 Technical Meeting, 13-14 June, 2012

Hotel Capo D’AfricaRome, Italy

Authors’ affiliations:IFPRI: Guush Berhane, Ruth Vargas Hill, Alemayehu Seyoum TaffesseOxford University: Daniel Clarke (also WB), Stefan Dercon (also DFID),

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Introduction Weather risk remains a major challenge to farming in the

developing world;

Thin insurance possibilities. Informal insurance hampered by risk covariance;

Classical information asymmetry problems and high implementation costs limit viability of traditional insurance;

Index-based weather insurance offers new possibilities;

However, demand remains invariably low – basis-risk – a key challenge;

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Steps taken to mitigate basis risk still limited;

Study Question – whether and how local traditional risk-sharing institutions – Iddirs in Ethiopia - can help mitigate basis risk ;

Study approach - randomized field experiment with an index product, an MFI, and Iddirs .

Study objective - explore possibilities that such risk-sharing institutions:

can be harnessed to mitigate basis risk; and

can, at the same time, become resilient to the ever changing climatic and environmental challenges.

Introduction

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Research questions

Specific questions:

1. Can group contracts mitigate basis risk by increasing side-payments in the event of individual-specific bad outcomes?

2. Do group contracts require ex-ante rules to effectively mitigate basis risk?

3. What are the mechanisms through which these processes work and what determines the direction of the outcome?

4. What are the overall welfare effects?

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Long run pilot—looking at group institutions takes time

first year in 2011, second year piloting now and continues!

57 Kebeles (3-4 villages) selected around 3 weather stations in Oromia region of Ethiopia – Shashemene, Dodota and Tibe

Primary interest is to target risk-sharing group

conducted a network mapping exercise to ensure selection of villages with low prob. of network overlap between “treatment” and “control” villages.

Weather index pilot in Ethiopia

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57 Kebeles(110 Villages)

TREATMENT(60 villages)

CONTROL(50 villages)

INDIVIDUAL(25 villages)

GROUP(35 villages)

MANDATED(18 villages)

NON-MANDATED(17 villages)

RANDOMIZATION

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Summary

  Control Individual Iddir, mandated Iddir, not mandated

Common

 

Insurance to individuals; all season (mobilization through iddir)

Insurance to iddirs; all season; iddir had to define rules

Insurance to iddirs; all season; iddir had to have a discussion

50 Birr (paid in Oct) to 16 randomly selected individuals

800 Birr (paid in Oct) to iddir to distribute

800 Birr (paid in Oct) to iddir to distribute

Shashemene

Meskerem insurance sold and prices varied across villages

Meskerem insurance was sold and prices varied across villages

Meskerem insurance was sold and prices varied across villages

October payout to those who bought

October payout to those who bought

October payout to those who bought

Dodota and Tibe

Meskerem insurance given to 16 randomly selected individuals

16 Meskerem insurance policies given to iddir

16 Meskerem insurance policies given to iddir

No payouts No payouts No payouts

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Summary Implication 1:

regressions on full sample with village randomization estimate the effect of the common elements throughout and the weighted combination of the different elements in Shashemene and elsewhere - separate results by location preferable.

Implication 2:

village treatment effects capture the joint impact of how insurance was marketed, how 800 Birr was distributed, and how 16 insurance policies were distributed (individual village treatmenin Dodota and Tibe). Specifically, effects could come as a result of:

Marketing/training/rule changes;

Something to disburse in iddir villages and randomly selected individuals in individual villages;

Having insurance – in Dotota and Tibe some individuals in individual villages received free insurance and in Shashemene the probability of buying insurance was likely affected by village;

Having savings – some individuals in individual villages received free savings;

No control for the method of distribution being different, but can control for whether or not someone was randomly given insurance or savings:

In Shashemene: include a dummy which takes the value of 1 if received individual savings;

In Dodota and Tibe: include a dummy which takes the value of 1 if received individual savings and dummy which takes the value of 1 if you received insurance;

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Mandated sharing-rules

What did we mandate?

The group establishes regular savings to a common pot;

A 10% of any insurance payout in this group goes to this pot;

This pool is disbursed to members that experience idiosyncratic basis risk, as a zero-interest loan;

Disbursement criteria is discussed and set by the group at the beginning of the year;

Members apply for the loan, group follows disbursement rules!

Repayment is enforced as per the rules;

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Money was contributed by project as “savings” Research goal: examine how money is disbursed – need to see

disbursements – and also show we keep our word - trust! Discussing and agreeing on bylaws is a time-consuming process, it

helped to have a reason to do this;

Disbursement procedures Iddir villages: In July/August Iddirs received a promise of 800 Birr in

October on completion of bylaws discussion; o Mandated: 800 Birr on completion of mandated form agreeing to how

payment would be spent;o Non-mandated: 800 Birr on completion of discussion, form could state that a

discussion would be held in the future on how to split payment;

Individual villages: In July/August 16 individuals were randomly selected in a public meeting to receive 50 Birr each in October;

Total flow of money into the village is the same, but who receives it is different;

Provision of savings

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Village-level meetings and training:

iddir leaders and influential people;

everyone in the village – organized through iddir leaders and village elders;

Very few early season (May, June and July) polices were sold;

Discounts offered for late season policies (September/Meskerem):

Free insurance in Dodota and Bako Tibe;

Price discounts in Shashemene: 40%, 60%, and 80% discounts randomly allocated across villages;

296 policies were sold in Shashemene (134 individuals and 435 Iddir members), about 13% of households;

Insurance Marketing, Sales, and Take-up

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September rains were poor in Shashemene – index triggered a payout!

Insurance payout was made at the end of October in Shashemene.

“Savings” payouts were also made at the end of October in all three sites.

Payouts

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Data

Baseline survey: February –March 2011:

1760 households in 110 villages (16 households per village);

Follow up survey I: December 2011, some weeks after payouts were made:

1734 households in 110 village re-visited (very little attrition, 1.5%);

138 iddirs in 110 villages;

Follow up survey II: February-March 2012;

Follow up survey III: February-March 2013;

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Baseline characteristics High incidence of drought: 51% experienced drought shock in the

last three years;

Formal insurance an almost unknown concept: 10% had heard about traditional indemnity (car, life or health) insurance; No-one had heard of weather or crop insurance before;

Also: Only 21% have heard of what a millimeter is; Only 7% had a bank account;

Initial interest in index-type insurance: 87% were interested in a weather indexed insurance policy described to them

in the survey;

Indications of huge basis risk: only 32% thought rainfall measured at the nearest weather station accurately

measured rainfall on their plots;

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Informal insurance very prevalent: only 5% did not belong to an iddir; 92% belonged to 1-5 iddirs

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0 2 4 6 8d1_how many iddir are you or members of your household a member of?

Baseline characteristics

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this village other village in this kebele nearby kebele elsewhered6_location of iddir

Close to 80% of iddirs’ span within the village

Baseline characteristics

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compare outcomes between the control and the following treatment groups: Individual and iddir Mandated and non-mandated iddirs

estimate the ANCOVA for outcome variables of interest with baseline data:

estimate a difference in outcome equation for outcome variables of interest without baseline data:

Stratification at location (weather station-level) so dummies are included for this in all regressions

Randomization at village level, so standard errors are clustered at the village level

Analysis

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Insurance Uptake

iddir_mandate 0.108**0.053

individual 0.077*0.039

cons 0.0230.014

Observations 387R-squared 0.019

Results for all individuals in treated villages in Shashemene - the omitted treatment is iddir_nomandate.

individuals in both iddir_mandate and individual villages purchased more insurance.

no statistical difference between iddir_mandate and individual villages in the amount of insurance purchased, although the point estimate for iddir_mandate is higher.

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Change in iddir rules

  Does your iddir provide

loans loans for crop loss

Iddir 0.061 0.066(0.046) (0.041)

Individual 0.071 0.042(0.044) (0.031)

Estimation method ANCOVA ANCOVAObservations 3629 3850R-squared 0.198 0.013District dummies included to account for stratification. Robust standard errors in parentheses

Change in iddir rules: No clear difference between iddirs in “iddir” treatment and “individual”

treatment villages; Reason - because we are combining mandated and non-mandated iddirs

(see below);

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Access to loans and transfers

  1 2 3 4 5 6

If your household needed 4,000 Birr for a medical emergency could the household obtain it within a week?

If your household needed 1,000 Birr for a medical emergency could the household obtain it within a week?

 insurance 0.066* 0.110***

0.034 0.037Iddir 0.101** 0.159***

0.038 0.041Individual 0.036 0.036 0.057 0.057

0.042 0.042 0.039 0.039savings -0.107 -0.107 0.019 0.018

-0.088 -0.088 0.132 0.132iddir_nomandate 0.055 0.136**

0.051 0.053iddir_mandate 0.139*** 0.178***

0.037 0.043Constant 0.258*** 0.257*** 0.256*** 0.548*** 0.543*** 0.543***

0.036 0.036 0.036 0.038 0.038 0.038Observations 1,107 1,107 1,107 1,107 1,107 1,107R-squared 0.018 0.023 0.026 0.036 0.045 0.046

Insurance increased perceived ability to finance emergencies; Result is driven by changes in the iddir villages, particularly changes in the mandated villages

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Access to loans and transfers

  7 8 9If your household needed 4,000 Birr to

start a business could the household obtain it within a week?

 insurance 0.043

0.03Iddir 0.038

0.032Individual 0.058 0.058

0.039 0.039savings -0.14 -0.14

-0.089 -0.089iddir_nomandate 0.019

0.028iddir_mandate 0.054

0.043Constant 0.164*** 0.164*** 0.165***

0.03 0.03 0.03Observations 1,105 1,105 1,105R-squared 0.03 0.032 0.033

Insurance did not increase perceived ability to finance a new business;

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Source of finance for small emergencies (Birr1000 with in a week) Those in mandated iddir villages reported increases in possible financing from

iddirs, friends and own assets.

Those in non-mandated iddir villages reported increases in financing from friends and own assets only.

Those in individual villages also reported increases in financing from iddirs (not sure why this would be).

Comparing the Shashemene and non-Shashemene - in the non Shashemene sites:

insurance did not increase a household’s ability to finance emergencies - if anything there was a lower ability of those in individual villages to rely on each other;

And perhaps a lower ability of those in mandated iddir villages to rely on friends;

Since the story is different in the non-Shashemene sites, the results thus suggests that it was the payout plus the mechanism that mattered;

Access to loans and transfers

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Question - Did these (insurance purchases, iddir discussions and changes in sharing rules within village) result in differences in welfare across study villages?

 Where there were payouts (Shashemene):

no effect on food consumption (baseline and round 1 only);

those in mandated villages were more able to purchase clothing, footwear and mobile phones in the 4-5 months following payouts than those in control villages.

no such differences between the individual and control villages, or the non-mandated iddirs and control villages.

Where there were no payouts (non-Shashemene sites):

no effect on food consumption;

no impact on durable purchases;

Impact on welfare (even more preliminary)

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Observations Specific questions:

1. Can group contracts mitigate basis risk by increasing side-payments in the event of individual-specific bad outcomes? - possible

2. Do group contracts require ex-ante rules to effectively mitigate basis risk? – they help

3. What are the mechanisms through which these processes work and what determines the direction of the outcome? – mandated rules, access to funds

4. What are the overall welfare effects? – some gains

Next steps, this season:

Continue with sharing rules and observe an additional season of insurance.

Included a feature to the index – i.e., gap insurance. A carefully designed crop-cutting experiment is added to the index.

A lot of optimism this year – many policies already sold, particularly in area where payouts made last year

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Thank you